379 resultados para Intelligent Environments
Resumo:
This paper presents an enhanced algorithm for matching laser scan maps using histogram correlations. The histogram representation effectively summarizes a map's salient features such that pairs of maps can be matched efficiently without any prior guess as to their alignment. The histogram matching algorithm has been enhanced in order to work well in outdoor unstructured environments by using entropy metrics, weighted histograms and proper thresholding of quality metrics. Thus our large-scale scan-matching SLAM implementation has a vastly improved ability to close large loops in real-time even when odometry is not available. Our experimental results have demonstrated a successful mapping of the largest area ever mapped to date using only a single laser scanner. We also demonstrate our ability to solve the lost robot problem by localizing a robot to a previously built map without any prior initialization.
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As the society matures, there was an increasing pressure to preserve historic buildings. The economic cost in maintaining these important heritage legacies has become the prime consideration of every state. Dedicated intelligent monitoring systems supplementing the traditional building inspections will enable the stakeholder to carry out not only timely reactive response but also plan the maintenance in a more vigilant approach; thus, preventing further degradation which was very costly and difficult to address if neglected. The application of the intelligent structural health monitoring system in this case studies of ‘modern heritage’ buildings is on its infancy but it is an innovative approach in building maintenance. ‘Modern heritage’ buildings were the product of technological change and were made of synthetic materials such as reinforced concrete and steel. Architectural buildings that was very common in Oceania and The Pacific. Engineering problems that arose from this type of building calls for immediate engineering solution since the deterioration rate is exponential. The application of this newly emerging monitoring system will improve the traditional maintenance system on heritage conservation. Savings in time and resources can be achieved if only pathological results were on hand. This case study will validate that approach. This publication will serve as a position paper to the on-going research regarding application of (Structural Health Monitoring) SHM systems to heritage buildings in Brisbane, Australia. It will be investigated with the application of the SHM systems and devices to validate the integrity of the recent structural restoration of the newly re-strengthened heritage building, the Brisbane City Hall.
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This paper reviews a variety of advanced signal processing algorithms that have been developed at the University of Southampton as part of the Prometheus (Programme for European traffic flow with highest efficiency and unprecedented safety) programme to achieve an intelligent driver warning system (IDWS). The IDWS includes the detection of road edges, lanes, obstacles and their tracking and identification, estimates of time to collision, and behavioural modelling of drivers for a variety of scenarios. The underlying algorithms are briefly discussed in support of the IDWS.
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This paper reviews a variety of advanced signal processing algorithms that have been developed at the University of Southampton as part of the Prometheus (PROgraMme for European Traffic flow with Highest Efficiency and Unprecedented Safety) research programme to achieve an intelligent driver warning system (IDWS). The IDWS includes: visual detection of both generic obstacles and other vehicles, together with their tracking and identification, estimates of time to collision and behavioural modelling of drivers for a variety of scenarios. These application areas are used to show the applicability of neurofuzzy techniques to the wide range of problems required to support an IDWS, and for future fully autonomous vehicles.
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Objective Explosive ordnance disposal (EOD) often requires technicians to wear multiple protective garments in challenging environmental conditions. The accumulative effect of increased metabolic cost coupled with decreased heat dissipation associated with these garments predisposes technicians to high levels of physiological strain. It has been proposed that a perceptual strain index (PeSI) using subjective ratings of thermal sensation and perceived exertion as surrogate measures of core body temperature and heart rate, may provide an accurate estimation of physiological strain. Therefore, this study aimed to determine if the PeSI could estimate the physiological strain index (PSI) across a range of metabolic workloads and environments while wearing heavy EOD and chemical protective clothing. Methods Eleven healthy males wore an EOD and chemical protective ensemble while walking on a treadmill at 2.5, 4 and 5.5 km·h− 1 at 1% grade in environmental conditions equivalent to wet bulb globe temperature (WBGT) 21, 30 and 37 °C. WBGT conditions were randomly presented and a maximum of three randomised treadmill walking trials were completed in a single testing day. Trials were ceased at a maximum of 60-min or until the attainment of termination criteria. A Pearson's correlation coefficient, mixed linear model, absolute agreement and receiver operating characteristic (ROC) curves were used to determine the relationship between the PeSI and PSI. Results A significant moderate relationship between the PeSI and the PSI was observed [r = 0.77; p < 0.001; mean difference = 0.8 ± 1.1 a.u. (modified 95% limits of agreement − 1.3 to 3.0)]. The ROC curves indicated that the PeSI had a good predictive power when used with two, single-threshold cut-offs to differentiate between low and high levels of physiological strain (area under curve: PSI three cut-off = 0.936 and seven cut-off = 0.841). Conclusions These findings support the use of the PeSI for monitoring physiological strain while wearing EOD and chemical protective clothing. However, future research is needed to confirm the validity of the PeSI for active EOD technicians operating in the field.
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Improving safety at railway level crossings is an important issue for the Australian transport system. Governments, the rail industry and road organisations have tried a variety of countermeasures for many years to improve railway level crossing safety. New types of Intelligent Transport System (ITS) interventions are now emerging due to the availability and the affordability of technology. These interventions target both actively and passively protected railway level crossings and attempt to address drivers’ errors at railway crossings, which are mainly a failure to detect the crossing or the train and misjudgement of the train approach speed and distance. This study aims to assess the effectiveness of three emerging ITS that the rail industry considers implementing in Australia: a visual in-vehicle ITS, an audio in-vehicle ITS, as well as an on-road flashing beacons intervention. The evaluation was conducted on an advanced driving simulator with 20 participants per trialled technology, each participant driving once without any technology and once with one of the ITS interventions. Every participant drove through a range of active and passive crossings with and without trains approaching. Their speed approach of the crossing, head movements and stopping compliance were measured. Results showed that driver behaviour was changed with the three ITS interventions at passive crossings, while limited effects were found at active crossings, even with reduced visibility. The on-road intervention trialled was unsuccessful in improving driver behaviour; the audio and visual ITS improved driver behaviour when a train was approaching. A trend toward worsening driver behaviour with the visual ITS was observed when no trains were approaching. This trend was not observed for the audio ITS intervention, which appears to be the ITS intervention with the highest potential for improving safety at passive crossings.
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Many complex aeronautical design problems can be formulated with efficient multi-objective evolutionary optimization methods and game strategies. This book describes the role of advanced innovative evolution tools in the solution, or the set of solutions of single or multi disciplinary optimization. These tools use the concept of multi-population, asynchronous parallelization and hierarchical topology which allows different models including precise, intermediate and approximate models with each node belonging to the different hierarchical layer handled by a different Evolutionary Algorithm. The efficiency of evolutionary algorithms for both single and multi-objective optimization problems are significantly improved by the coupling of EAs with games and in particular by a new dynamic methodology named “Hybridized Nash-Pareto games”. Multi objective Optimization techniques and robust design problems taking into account uncertainties are introduced and explained in detail. Several applications dealing with civil aircraft and UAV, UCAV systems are implemented numerically and discussed. Applications of increasing optimization complexity are presented as well as two hands-on test cases problems. These examples focus on aeronautical applications and will be useful to the practitioner in the laboratory or in industrial design environments. The evolutionary methods coupled with games presented in this volume can be applied to other areas including surface and marine transport, structures, biomedical engineering, renewable energy and environmental problems.
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Programming is a subject that many beginning students find difficult. The PHP Intelligent Tutoring System (PHP ITS) has been designed with the aim of making it easier for novices to learn the PHP language in order to develop dynamic web pages. Programming requires practice. This makes it necessary to include practical exercises in any ITS that supports students learning to program. The PHP ITS works by providing exercises for students to solve and then providing feedback based on their solutions. The major challenge here is to be able to identify many semantically equivalent solutions to a single exercise. The PHP ITS achieves this by using theories of Artificial Intelligence (AI) including first-order predicate logic and classical and hierarchical planning to model the subject matter taught by the system. This paper highlights the approach taken by the PHP ITS to analyse students’ programs that include a number of program constructs that are used by beginners of web development. The PHP ITS was built using this model and evaluated in a unit at the Queensland University of Technology. The results showed that it was capable of correctly analysing over 96 % of the solutions to exercises supplied by students.
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Robustness to variations in environmental conditions and camera viewpoint is essential for long-term place recognition, navigation and SLAM. Existing systems typically solve either of these problems, but invariance to both remains a challenge. This paper presents a training-free approach to lateral viewpoint- and condition-invariant, vision-based place recognition. Our successive frame patch-tracking technique infers average scene depth along traverses and automatically rescales views of the same place at different depths to increase their similarity. We combine our system with the condition-invariant SMART algorithm and demonstrate place recognition between day and night, across entire 4-lane-plus-median-strip roads, where current algorithms fail.
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There is currently a lack of reference values for indoor air fungal concentrations to allow for the interpretation of measurement results in subtropical school settings. Analysis of the results of this work established that, in the majority of properly maintained subtropical school buildings, without any major affecting events such as floods or visible mould or moisture contamination, indoor culturable fungi levels were driven by outdoor concentration. The results also allowed us to benchmark the “baseline range” concentrations for total culturable fungi, Penicillium spp., Cladosporium spp. and Aspergillus spp. in such school settings. The measured concentration of total culturable fungi and three individual fungal genera were estimated using Bayesian hierarchical modelling. Pooling of these estimates provided a predictive distribution for concentrations at an unobserved school. The results indicated that “baseline” indoor concentration levels for indoor total fungi, Penicillium spp., Cladosporium spp. and Aspergillus spp. in such school settings were generally ≤ 1450, ≤ 680, ≤ 480 and ≤ 90 cfu/m3, respectively, and elevated levels would indicate mould damage in building structures. The indoor/outdoor ratio for most classrooms had 95% credible intervals containing 1, indicating that fungi concentrations are generally the same indoors and outdoors at each school. Bayesian fixed effects regression modeling showed that increasing both temperature and humidity resulted in higher levels of fungi concentration.
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There’s growing evidence that psychosis is linked to the physical environments that we live in. Good environments are the ones that allow people to step back, relax and feel secure, while engaging in interesting and meaningful activity. Bad environments don’t allow respite: they keep people on their toes and somehow magnify meaninglessness and hollow rules and unreasonable demands. They may also be bleak and even unfair or outright scary. But don’t expect everyone to notice the bad environments: recent studies demonstrate that patients with psychosis are far more likely to notice even subtle negative features in the environment than people without symptoms. The same patients are also less likely to notice the good things an environment has to offer – but that doesn’t mean they shouldn’t be provided.
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This chapter is focussed on the research and development of an intelligent driver warning system (IDWS) as a means to improve road safety and driving comfort. Two independent IDWS case studies are presented. The first study examines the methodology and implementation for attentive visual tracking and trajectory estimation for dynamic scene segmentation problems. In the second case study, the concept of driver modelling is evaluated which can be used to provide useful feedback to drivers. In both case studies, the quality of IDWS is largely determined by the modelling capability for estimating multiple vehicle trajectories and modelling driving behaviour. A class of modelling techniques based on neural-fuzzy systems, which exhibits provable learning and modelling capability, is proposed. For complex modelling problems where the curse of dimensionality becomes an issue, a network construction algorithm based on Adaptive Spline Modelling of Observation Data (ASMOD) is also proposed.
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This paper examines the role and importance of international business experience for firms operating in technologically-mediated environments. Although the key success factors of international expansion have been subject to extensive research in the international business literature, the analysis of technology-mediated environments on international business experience remains limited. This finding is unexpected given that the Internet and the technologies that have enabled it have profoundly transformed the ways in which international business is conducted. This is especially so for firms in the Australian region where the Internet has allowed business to access the scale of markets they need to grow and operate globally (Google and PWC, 2015). Given that businesses of the future will need to innovate quicker and more effectively in online settings to remain competitive, it seems appropriate that we re-visit the more traditional facets of internationalisation; such as the necessity of international business experience for firm performance. In doing so, the empirical section of this paper focuses on twelve Australian international entrepreneurial firms, who in varying degrees utilise technology to leverage their internationalisation activities. The findings suggest that international entrepreneurs with lower levels of international business experience still achieve international performance outcomes. The findings indicate that firms are recognising that the ability to adapt and evolve quickly in technologically-advanced settings is imperative. The findings also suggest that international entrepreneurs are relying less on traditional facets of international business experience, and are learning in self-taught or autodidactic ways. This is because businesses in the current global climate are now operating in complex and highly dynamic environments, characterised by rapid change; thus, the findings suggest that international business experience is becoming less important due to the evolving nature of international business environments.
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The provision of autonomy supportive environments that promote physical activity engagement have become popular in contemporary youth settings. However, questions remain about whether adolescent perceptions of their autonomy have implications for physical activity. The purpose of this investigation was to examine the association between adolescents’ self-reported physical activity and their perceived autonomy. Participants (n = 384 adolescents) aged between 12 and 15 years were recruited from six secondary schools in metropolitan Brisbane, Australia. Self-reported measures of physical activity and autonomy were obtained. Logistic regression with inverse probability weights were used to examine the association between autonomy and the odds of meeting youth physical activity guidelines. Autonomy (OR 0.61, 95% CI 0.49-0.76) and gender (OR 0.62, 95% CI 0.46-0.83) were negatively associated with meeting physical activity guidelines. However, the model explained only a small amount of the variation in whether youth in this sample met physical activity guidelines (R2 = 0.023). For every 1 unit decrease in autonomy (on an index from 1 to 5), participants were 1.64 times more likely to meet physical activity guidelines. The findings, which are at odds with several previous studies, suggest that interventions designed to facilitate youth physical activity should limit opportunities for youth to make independent decisions about their engagement. However, the small amount of variation explained by the predictors in the model is a caveat, and should be considered prior to applying such suggestions in practical settings. Future research should continue to examine a larger age range, longitudinal observational or intervention studies to examine assertions of causality, as well as objective measurement of physical activity.
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This paper presents a novel vision-based underwater robotic system for the identification and control of Crown-Of-Thorns starfish (COTS) in coral reef environments. COTS have been identified as one of the most significant threats to Australia's Great Barrier Reef. These starfish literally eat coral, impacting large areas of reef and the marine ecosystem that depends on it. Evidence has suggested that land-based nutrient runoff has accelerated recent outbreaks of COTS requiring extensive use of divers to manually inject biological agents into the starfish in an attempt to control population numbers. Facilitating this control program using robotics is the goal of our research. In this paper we introduce a vision-based COTS detection and tracking system based on a Random Forest Classifier (RFC) trained on images from underwater footage. To track COTS with a moving camera, we embed the RFC in a particle filter detector and tracker where the predicted class probability of the RFC is used as an observation probability to weight the particles, and we use a sparse optical flow estimation for the prediction step of the filter. The system is experimentally evaluated in a realistic laboratory setup using a robotic arm that moves a camera at different speeds and heights over a range of real-size images of COTS in a reef environment.